As part of interactive data exploration, researchers may need to compare multiple datasets.
These datasets can originate from various independent files or generative models that need
to be compared with reality. When these datasets are of high dimensionality, especially if
the exploration is tentative, developing tailored statistical tests can become impractical.
In those cases, relying on heuristic approaches based on machine learning techniques as
classifiers to decide whether two samples are distinguishable becomes a good
alternative [1]}, [2]}.
